Top Machine Learning Jobs in Vancouver

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

The Technical Solutions Manager bridges Sales and Software Engineering, leading technical discovery, designing solutions, and engaging customers to drive revenue growth.

Own product strategy and execution for discovery, navigation, and presentation of bias/factuality signals. Drive experiments, analyze metrics, and partner with engineering, design, ML, marketing, and analytics to improve engagement, conversion, and retention for a consumer subscription product across mobile and web.

Join an ASIC design team to develop and implement ASIC flows, automate design processes with scripting, perform synthesis and rule checking, and support design tasks for coherent optics chips while learning and collaborating with engineers.

Lead architecture and delivery of production-grade applied AI systems (LLMs, retrieval, agents). Solve cross-stack technical problems, define platform direction on AWS, optimize data and database design, improve quality/QA and observability, mentor a ~20-person team, and translate ambiguous product opportunities into measurable technical outcomes.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

The Solutions Engineer supports the sales team by providing technical expertise, conducting demonstrations, designing solutions, and managing complex integrations during the sales cycle.

Own the Move Money Platform roadmap and execution globally: define network strategy for fiat and crypto rails, design routing and resiliency, manage network integrations and compliance, lead engineering through SDLC, apply AI for smarter routing and operations, and represent Versapay with partners and regulators.

Lead end-to-end delivery of large-scale, technically complex customer programs for Phaidra's industrial AI control systems. Own program strategy, customer relationships, cross-functional coordination, risk mitigation, documentation, and continuous process improvements while mentoring TPMs and aligning product and engineering to customer needs.

Lead and grow a team of Technical Program Managers who run customer data projects end-to-end: staffing cadence, project setup, throughput and margin tracking, AR/billing hygiene, Airtable as system of record, onboarding TPMs, operational playbooks, and escalation for delivery risk. Serve as a player-coach partnering with Deployment Leads, FDE Manager, and GMs to ensure projects are staffed and delivered reliably.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The role involves designing and deploying strategies for congestion revenue rights, applying quantitative methods, and developing machine learning models.

As Staff Product Manager for the AI Platform, you'll define the vision and roadmap, establish execution methods, and collaborate across teams to ensure safe and efficient AI operations in a scalable enterprise platform.

Partner with portfolio and risk managers to develop quantitative risk models, analyze U.S. power markets, improve backtesting and simulation infrastructure, attribute performance, track P&L and exposures, and deliver actionable insights to scale the trading and risk platform.

Lead horizon scanning and external intelligence to identify AI and disruptive tech opportunities for R&D. Translate trends into actionable briefs, design and run pilots with stage-gates, and scale successful capabilities into production. Influence senior leadership with strategic foresight, build external partnerships, and embed a future-back innovation culture across cross-functional teams to measurably improve R&D outcomes.

Provide commercial legal support across Sales, Product, Partnerships, Procurement, and Engineering: draft and negotiate NDAs, SaaS and vendor agreements, advise on product and privacy/regulatory risks (GDPR, CCPA/CPRA, GLBA), improve contract lifecycle management, and respond to day-to-day legal inquiries and ad hoc projects.

Lead platform product ownership across cloud and firmware, translate business and customer requirements into prioritized backlogs, collaborate with R&D and stakeholders, define release content, and drive agile execution to deliver platform product increments aligned with strategy.

The role involves conducting research and optimizing machine learning systems while collaborating with technical staff to enhance product performance.

As a Research/ML Engineer, you will translate cutting-edge AI research into product solutions, develop safety and reliability systems, and collaborate with technical teams.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

Design and build data architectures, oversee ETL/ELT pipelines, collaborate with stakeholders to optimize data usage, and implement data quality frameworks.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.